Forecasting the Severity of COVID-19 Pandemic Amidst the Emerging SARS-CoV-2 Variants: Adoption of ARIMA Model

Comput Math Methods Med. 2022 Jan 13:2022:3163854. doi: 10.1155/2022/3163854. eCollection 2022.

Abstract

Currently, the global report of COVID-19 cases is around 110 million, and more than 2.43 million related death cases as of February 18, 2021. Viruses continuously change through mutation; hence, different virus of SARS-CoV-2 has been reported globally. The United Kingdom (UK), South Africa, Brazil, and Nigeria are the countries from which these emerged variants have been notified and now spreading globally. Therefore, these countries have been selected as a research sample for the present study. The datasets analyzed in this study spanned from March 1, 2020, to January 31, 2021, and were obtained from the World Health Organization website. The study used the Autoregressive Integrated Moving Average (ARIMA) model to forecast coronavirus incidence in the UK, South Africa, Brazil, and Nigeria. ARIMA models with minimum Akaike Information Criterion Correction (AICc) and statistically significant parameters were chosen as the best models in this research. Accordingly, for the new confirmed cases, ARIMA (3,1,14), ARIMA (0,1,11), ARIMA (1,0,10), and ARIMA (1,1,14) models were chosen for the UK, South Africa, Brazil, and Nigeria, respectively. Also, the model specification for the confirmed death cases was ARIMA (3,0,4), ARIMA (0,1,4), ARIMA (1,0,7), and ARIMA (Brown); models were selected for the UK, South Africa, Brazil, and Nigeria, respectively. The results of the ARIMA model forecasting showed that if the required measures are not taken by the respective governments and health practitioners in the days to come, the magnitude of the coronavirus pandemic is expected to increase in the study's selected countries.

MeSH terms

  • Brazil / epidemiology
  • COVID-19 / epidemiology*
  • COVID-19 / virology*
  • Computational Biology
  • Confidence Intervals
  • Epidemiological Models*
  • Forecasting / methods
  • Humans
  • Incidence
  • Models, Statistical
  • Nigeria / epidemiology
  • Pandemics* / statistics & numerical data
  • Regression Analysis
  • SARS-CoV-2* / genetics
  • SARS-CoV-2* / pathogenicity
  • Severity of Illness Index
  • South Africa / epidemiology
  • United Kingdom / epidemiology

Supplementary concepts

  • SARS-CoV-2 variants